ee.ConfusionMatrix.array

  • The ConfusionMatrix.array() function returns the confusion matrix as an ee.Array object.

  • This function is used to access the underlying data of an ee.ConfusionMatrix object for further analysis or visualization.

  • The confusion matrix represents the performance of a classifier, with rows indicating actual values and columns indicating predicted values.

  • You can create an ee.ConfusionMatrix from an existing ee.Array or by using the ee.Classifier.confusionMatrix() function.

 Returns a confusion matrix as an Array.

UsageReturns
ConfusionMatrix.array()Array
ArgumentTypeDetails
this: confusionMatrixConfusionMatrix

Examples

Code Editor (JavaScript)

// Construct a confusion matrix from an array (rows are actual values,
// columns are predicted values). We construct a confusion matrix here for
// brevity and clear visualization, in most applications the confusion matrix
// will be generated from ee.Classifier.confusionMatrix.
var array = ee.Array([[32, 0, 0,  0,  1, 0],
                      [ 0, 5, 0,  0,  1, 0],
                      [ 0, 0, 1,  3,  0, 0],
                      [ 0, 1, 4, 26,  8, 0],
                      [ 0, 0, 0,  7, 15, 0],
                      [ 0, 0, 0,  1,  0, 5]]);
var confusionMatrix = ee.ConfusionMatrix(array);
print("ee.ConfusionMatrix", confusionMatrix);

print("ee.ConfusionMatrix as ee.Array", confusionMatrix.array());

Python setup

See the Python Environment page for information on the Python API and using geemap for interactive development.

import ee
import geemap.core as geemap

Colab (Python)

from pprint import pprint

# Construct a confusion matrix from an array (rows are actual values,
# columns are predicted values). We construct a confusion matrix here for
# brevity and clear visualization, in most applications the confusion matrix
# will be generated from ee.Classifier.confusionMatrix.
array = ee.Array([[32, 0, 0,  0,  1, 0],
                  [ 0, 5, 0,  0,  1, 0],
                  [ 0, 0, 1,  3,  0, 0],
                  [ 0, 1, 4, 26,  8, 0],
                  [ 0, 0, 0,  7, 15, 0],
                  [ 0, 0, 0,  1,  0, 5]])
confusion_matrix = ee.ConfusionMatrix(array)
print("ee.ConfusionMatrix:")
pprint(confusion_matrix.getInfo())

print("ee.ConfusionMatrix as ee.Array:")
pprint(confusion_matrix.array().getInfo())